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CPG glossary

Everyday low price (EDLP) vs Hi-Lo pricing

What everyday low price means

Everyday low price (EDLP) is a retail pricing strategy of holding shelf prices steady and low all the time, instead of bouncing between high regular prices and deep temporary discounts. The basic price a shopper sees is the price they will keep seeing. Walmart built its entire brand on it, and Costco runs a version of the same idea: the price you see this week is roughly the price you'll see next week. The opposite approach, Hi-Lo, is what Kroger and most conventional grocery run: a higher base price punctuated by frequent promotions, coupons, and circular features.

If you sell into both kinds of retailer, this isn't an academic distinction. The same SKU gets a completely different financial treatment depending on which model the retailer uses, and your trade spend behaves differently in each.

EDLP vs Hi-Lo on a single SKU

Take one product (a 10 oz jar of pasta sauce the brand sells to the retailer at $2.20 a unit) and run it through both models. Assume the retailer wants the same blended margin over a 4-week month.

LineEDLP (Walmart)Hi-Lo (Kroger)
Retailer cost per unit$2.20$2.20
Shelf price (regular)$2.99$3.49
Promoted price (1 wk/4)none$2.49
Blended shelf price$2.99$3.24
Units/store/week (avg)3026
Blended retailer margin~26.4%~32.1% on base weeks
Baseline (regular-price) volumePromoted volumeEDLP95% baselineHi-Lo65% baseline35% promoted
Hi-Lo leans far harder on promoted volume (35%) than EDLP (5%) - the core behavioral difference (worked example)

The EDLP shelf price ($2.99) never moves, so the shopper does no math and the retailer carries thinner per-unit retail margin in exchange for steadier volume. The Hi-Lo retailer prices higher most of the month ($3.49), then drops to $2.49 in the promo week to pull a spike. The blended price lands at $3.24, above the EDLP shelf, but it depends on shoppers paying full freight in the three non-promo weeks. Cherry-pickers who only buy on deal break that math.

Notice the volume line too. The steady EDLP price moves a bit more baseline (30 vs 26 units), but the Hi-Lo promo week can spike well past either when the discount hits. Different shapes, same goal.

What each model does to trade spend

This is the part brand-side analysts have to watch. Under Hi-Lo, your trade dollars fund the promo week directly: the $2.49 price needs a markdown, and the brand usually pays for it through an off-invoice allowance or a scan-based deal. That spend is visible, lumpy, and tied to specific weeks.

Under EDLP, there's often no week-to-week promotion to fund at all. Instead the retailer wants a lower everyday cost, so the "spend" shows up as a permanently reduced list price or an ongoing per-case allowance baked into the deal. It's quieter, but it never stops. A brand that's used to budgeting trade as a series of TPRs can underestimate the EDLP commitment because it doesn't arrive as discrete events.

The base-versus-promoted split tells the story:

Volume typeEDLP shareHi-Lo share
Baseline volume~95%~65%
Promoted volume~5%~35%

In a Hi-Lo account, a third or more of your units can move on deal, which means your reported velocity is partly bought. In an EDLP account, almost everything is baseline, so the velocity number is cleaner but the price ceiling is lower. When you compare a Walmart and a Kroger report side by side, you're comparing two different volume mixes, not just two prices.

Psychological pricing and price thresholds

Psychological pricing sets a shelf price for how it reads rather than what it computes to. The everyday form is charm pricing: ending on 9 so $2.99 lands as "two something" instead of three dollars. That is why almost every price in this page's examples ends in 9, and why a retailer moving a pasta sauce from $2.99 to $3.05 usually goes to $3.09 or $3.19 instead.

Threshold pricing is the version that actually shows up in your data. Demand does not slope smoothly across price. It steps at round numbers, because that is where the shopper re-evaluates. Take the same 10 oz jar across four test prices at a regional grocer:

Shelf priceUnits / store / weekChange vs prior step
$2.9930
$3.0929-3%
$3.1928-3%
$3.2922-21%
27 forecast30$2.9929$3.0928$3.1922$3.29threshold crossed: -21%units / store / week
Demand steps at round numbers: two dimes cost ~3% each, the third costs 21% (worked example)

The first two dimes cost almost nothing. The third one crosses a threshold the shopper is holding in their head and takes a fifth of the volume with it. If you model elasticity as a single slope across that range, you will forecast 27 units at $3.29 and be wrong by five units per store per week, every week.

For a brand-side analyst the practical rule is to test price changes against the nearest round number, not against a percentage. A 10-cent increase that stays under $3.00 and a 10-cent increase that crosses it are not the same experiment.

Zone pricing: one SKU, several shelf prices

Zone pricing, also called segment or geographic pricing, is a retailer charging different prices for the same item in different stores. Kroger does not price a Houston store the same as a Denver one, and a Manhattan banner runs above its suburban siblings in the same chain. The zone is usually built from local competition and cost to serve, not from anything the brand controls.

This matters because it quietly breaks the average price on your report. A banner that shows $3.28 as its average retail is not selling anything at $3.28:

ZoneStoresShelf priceUnits / store / weekUnit share
Urban40$3.492226%
Suburban90$3.192874%
Chain "average"130$3.2826100%

Nobody pays $3.28. The two real prices are 30 cents apart, and the cheaper zone is doing three quarters of the volume. If you read the blended number as the price and compare it to a competitor's blended number, you are comparing two different store mixes and calling it a price gap.

The fix is to segment before you compare. Pull price and units by zone or by store cluster where the data supports it, and benchmark like for like. Where it does not, at least know that the average is a weighted artifact, and say so on the slide before someone else does.

Why the distinction matters to an analyst

If you benchmark a SKU's performance across an EDLP and a Hi-Lo retailer without adjusting for the model, you'll draw the wrong conclusion. The Hi-Lo account looks like it has more "lift," but that lift is just the promo weeks; net out the trade spend and the picture often flips. The EDLP account looks flat and unpromoted, but its baseline is doing all the work, which is usually healthier for long-run margin.

The cleanest way to read it: separate baseline from promoted volume in every account, then compare baselines to baselines. That neutralizes the pricing model and shows you which retailer is actually building demand versus which one is renting it one promo week at a time. It also clarifies where your shopper marketing dollars do more good, since EDLP and Hi-Lo shoppers respond to very different signals.

Where Scout fits

The hard part of EDLP-vs-Hi-Lo analysis is splitting baseline from promoted volume consistently across retailers that price in completely different rhythms. Scout connects your SPINS or retailer data and reads each account on its own terms, so a flat EDLP line and a spiky Hi-Lo line become comparable. It measures and analyzes the result; it doesn't set your prices or execute the deals. It just keeps the comparison honest.

The short version

  • Everyday low price (EDLP) means steady low shelf prices all the time (Walmart, Costco), versus Hi-Lo's higher base price plus frequent deep promotions (Kroger, conventional grocery).
  • EDLP leans on baseline volume at thinner per-unit margin; Hi-Lo leans on promo-week spikes funded by visible trade spend, with a much larger promoted-volume share.
  • To compare a SKU across both, split baseline from promoted volume and benchmark baselines, or the Hi-Lo "lift" will fool you.

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